Understanding the pollution characteristics and formation mechanisms of winter haze episodes in China's megacity
Haze is an air pollution phenomenon where large amounts of fine particulate matter (such as PM2.5 and PM10) are suspended in the air, reducing visibility. These particles not only scatter and absorb light, affecting light source transmission and threatening road traffic safety, but also pose serious threats to human health.
According to data from the Shanghai Environmental Monitoring Center, in September 2025, the average PM2.5 concentration in Shanghai was 14.8 μg/m³, showing a slight year-on-year increase, but the overall excellent air quality rate remained at 93.3%2 . However, looking at the entire year, the city's average PM2.5 concentration from January to September was 25.3 μg/m³2 , indicating that in non-summer months, especially in winter, particulate matter concentrations increase significantly, and haze pollution becomes more frequent and severe.
Haze significantly reduces visibility, creating hazardous conditions for transportation and daily activities.
Fine particulate matter can penetrate deep into lungs, causing respiratory and cardiovascular problems.
To深入研究 haze environment下的光源透过性规律, scientists have designed a sophisticated experimental research device for light source transmittance in haze environments1 . This device can simulate haze environments under different conditions and comprehensively analyze the influence of various factors on light source transmittance.
The core device is a sealed rectangular box made of organic glass—the haze simulation experiment box. A test light source is installed on one side of the box, and a illuminance meter is installed at the corresponding position on the other side to measure the intensity change of light passing through the haze1 .
The experimental setup includes independent fog generation and haze generation devices.
This is the key to the experiment. Researchers can precisely control various environmental variables:
Under each set environment, record the readings of the illuminance meter, compare them with the baseline value in clean air, calculate the attenuation degree of light, and thus quantify the impact of haze on light source transmittance.
After the experiment, activate the air purification device to filter and remove the haze particles inside the box, ensuring the safety of experimental personnel and no pollution to the environment1 .
Through the above experiments, scientists found:
Concentration vs Visibility
Particle Size Impact
Meteorological Factors
Haze pollution does not uniformly cover the entire city; its concentration distribution shows obvious spatial differences. The following table compiles the monthly average concentrations of road PM10 mobile monitoring in various districts of Shanghai in September 2025 according to data from the Shanghai Environmental Monitoring Center2 :
| Administrative District | Road PM10 Concentration (μg/m³) |
|---|---|
| Jiading District | 77.2 |
| Songjiang District | 68.8 |
| Putuo District | 67.6 |
| Qingpu District | 67.6 |
| Changning District | 66.0 |
| Huangpu District | 65.8 |
| Jing'an District | 65.8 |
| Hongkou District | 65.6 |
| Baoshan District | 65.4 |
| Xuhui District | 65.0 |
| Yangpu District | 65.0 |
| Minhang District | 64.9 |
| Pudong New Area | 63.6 |
| Chongming District | 63.5 |
| Jinshan District | 63.4 |
| Fengxian District | 59.7 |
From the table, it can be seen that Jiading District, Songjiang District, Putuo District, and Qingpu District have relatively high road PM10 concentrations, while Fengxian District, Jinshan District, and Chongming District have lower concentrations. This spatial distribution is closely related to the industrial layout, traffic flow, and geographical diffusion conditions of the areas.
The pollution levels in certain specific road sections are particularly prominent. The following are the ten roads with the highest PM10 concentrations in September 20252 :
| Rank | Administrative District | Road Name | Section Average (μg/m³) |
|---|---|---|---|
| 1 | Chongming District | Tuancheng Highway | 236 |
| 2 | Songjiang District | Minta Highway | 222 |
| 3 | Jiading District | Huajiang Highway | 218 |
| 4 | Jing'an District | Hutai Road | 179 |
| 5 | Jinshan District | Qinwan Road | 172 |
| 6 | Putuo District | Wuwei Road | 167 |
| 7 | Jiading District | Ruilin Road | 161 |
| 8 | Jiading District | Yangchuan Road | 160 |
| 9 | Jinshan District | Xian'an Road | 150 |
| 10 | Jiading District | Shengxin North Road | 150 |
To do good work, one must first sharpen one's tools. Scientists rely on a series of advanced equipment and reagents to uncover the mysteries of haze. The following table lists some "scientific research artifacts" crucial in haze research and simulation experiments1 4 :
| Tool/Technology Name | Function Description |
|---|---|
| Aerosol Particle Size Spectrometer | Generates and precisely measures the particle size distribution of simulated haze particles, forming the basis for generating haze of specific composition1 . |
| Ultrasonic Humidifier | Generates micron-sized water mist droplets, used to simulate the high humidity environment of foggy days and liquid particulate matter1 . |
| Illuminance Meter | Core measurement tool that directly measures the light intensity after passing through the haze area, quantifying transmittance1 . |
| Temperature and Humidity Control System | Precisely simulates various meteorological conditions from low temperature and dry to high temperature and humid, studying the impact of temperature and humidity on haze formation and dissipation4 . |
| Wind Speed Control Device | Simulates natural wind through a fan system, studying the role of air movement in pollutant diffusion and aggregation processes1 . |
| Air Purification System | Ensures experimental safety, efficiently removes pollutants from enclosed spaces after experiments, protecting personnel and the environment1 . |
Controlled experiments allow researchers to isolate specific factors affecting haze formation and light transmission properties.
Real-world data collection provides validation for laboratory findings and reveals actual pollution patterns across the city.
In-depth research on haze characteristics and analysis of typical processes ultimately aim for better prediction and prevention. Shanghai continues to make efforts in technological innovation and policy guidance.
"The study of haze formation mechanisms provides scientific basis for effective pollution prevention and control, reminding us that protecting this blue sky requires the joint efforts of science, policy, and public awareness."
At the technological forefront, Shanghai's research teams are actively exploring more advanced solutions. For example, the Aerosol Intelligence Laboratory (AIL) led by Researcher Feng Jicheng from ShanghaiTech University is transforming aerosols, typically regarded as pollutants, into cutting-edge nanotechnology, providing innovative tools for various fields including environmental governance7 .
At the policy level, Shanghai and its districts are also actively promoting the construction of climate-resilient cities. For example, Chongming District, as a pilot, is advancing a series of projects to enhance the city's ability to cope with extreme weather and pollution events, aiming to build a safer, more livable, and sustainable urban environment.
Developing long-term strategies for pollution reduction and environmental protection.
Leveraging AI and IoT for smarter air quality monitoring and management.
Increasing awareness and participation in environmental protection initiatives.
Haze is the product of complex meteorological conditions and the interaction of various pollutants. Through precise simulation experiments, continuous monitoring data, and continuously innovative science and technology, we are gradually uncovering the formation mechanisms of winter haze in Shanghai. This not only provides a scientific basis for effective pollution prevention but also reminds us that protecting this blue sky requires the joint efforts of science, policy, and public awareness.
The experimental devices and methods cited in this article are primarily based on patent literature, used for principle explanation. Specific air quality data comes from government monitoring reports and is for reference only.